Engineering Manager, AI

Lattice is a people success platform dedicated to empowering organizations and their employees. They are seeking an Engineering Manager to lead the AI Intelligence Quality team, responsible for building the AI Platform that ensures quality and performance across all AI products.

Responsibilities:

• Lead, coach, and grow a high-performing team of AI and software engineers, developing them into strong technical leaders while fostering a culture of ownership, technical excellence, experimentation, and continuous learning
• Own the execution and delivery of the AI Platform roadmap, balancing near-term product impact with long-term platform investments
• Partner closely with Product, Applied AI, Data Science, and engineering leaders to define how AI quality is measured, evaluated, and continuously improved across Lattice
• Lead the development of AI evaluation infrastructure, quality metrics, experimentation capabilities, observability, and developer tooling that enable every AI product team to confidently build, evaluate, and ship AI experiences
• Drive technical and organizational decisions that improve the scalability, reliability, and adoption of the AI Platform, empowering engineers to own architecture and technical solutions
• Build strong cross-functional partnerships and influence engineering strategy to establish AI evaluations as a foundational capability that accelerates AI development across Lattice

Requirements:

• Experience leading and growing high-performing software engineering teams, with a track record of hiring, coaching, and developing engineers into strong technical leaders
• Strong technical background leading teams that build AI infrastructure, AI-powered products leveraging Large Language Models (LLMs) and/or AI agents, distributed systems, or developer platforms
• Experience building enterprise SaaS AI products where quality, trust, reliability, and scalability are critical to customer success
• Proven ability to lead complex cross-functional initiatives from strategy through execution, partnering effectively with Product, Applied AI, Data Science, and Engineering to deliver business impact
• Excellent communication and stakeholder management skills, with the ability to create clarity, align teams, and influence technical direction in fast-moving, ambiguous environments
• A strong product and platform mindset, balancing customer impact, engineering velocity, operational excellence, and long-term technical investments
• A leadership style grounded in curiosity, humility, ownership, and continuous learning, with a passion for building exceptional engineering teams and delivering high-quality AI products
• Experience building AI evaluation frameworks, experimentation platforms, or ML infrastructure
• Knowledge of statistical experimentation, A/B model testing, offline evaluations, or model benchmarking
• Familiarity with advanced AI optimization techniques such as Direct Preference Optimization (DPO), Reinforcement Learning from Human Feedback (RLHF), model fine-tuning, or preference learning
• Experience building internal platforms and services adopted across multiple engineering teams